Lohse Lab Shimadzu Data Parser

knitr::opts_chunk$set(echo = FALSE)
library(tidyverse)
library(DT)

Show/Hide Raw Data Table

# Load Shimadzu export file (.csv)
raw_df <- read.csv("data/RCEW_NPOCTN_20220315.csv", skip=10, as.is=T)

raw_df <- raw_df %>% mutate(DateTime = Date...Time)

datatable(raw_df, rownames = F,
            options = list(
              pageLength = 100))

# Process NPOC data

npoc_df <- raw_df %>% filter(!is.na(Result.NPOC.)) %>% 
            filter(Type != "Standard") %>% 
            select(Sample.Name, Sample.ID, Result.NPOC., Vial, DateTime)

npoc_blanks <- npoc_df %>% filter(grepl("BLANK", toupper(Sample.Name)))
### Blank correction???


npoc_checks <- suppressWarnings(npoc_df %>% filter(grepl("CCV", Sample.Name)) %>% 
                mutate(Sample.ID = as.numeric(Sample.ID)) %>%
                filter(!is.na(Sample.ID)) %>%
                mutate(Accuracy = round(Result.NPOC.*100/Sample.ID, 2))) %>%
                mutate(Note = ifelse(Accuracy < 95 | Accuracy > 105, 
                                     "***WARNING***", "GOOD"))

npoc_final <- npoc_df %>% filter(!grepl("BLANK", toupper(Sample.Name))) %>%
                filter(!grepl("CCV", Sample.Name)) %>%
                select(Sample.Name, Result.NPOC.)
### Blank correction???

Show/Hide NPOC Data Table

datatable(npoc_df, rownames = F,
            options = list(
              pageLength = 100))

Show/Hide NPOC Blanks

datatable(npoc_blanks, rownames = F,
            options = list(
              pageLength = 100))

NPOC Check Standards

datatable(npoc_checks, rownames = F,
            options = list(
              pageLength = 100))

Final NPOC Data

datatable(npoc_final, rownames = F,
          extensions = 'Buttons', options = list(
            pageLength = 100,
            dom = 'Bfrtip',
            buttons = 
              list('copy', 'print', list(
                extend = 'collection',
                buttons = c('csv', 'excel', 'pdf'),
                text = 'Download'
            ))))